import java.io.BufferedReader;
import java.io.FileReader;
import java.io.IOException;
import java.util.Date;
import java.util.HashMap;
import java.text.ParseException;
import java.text.SimpleDateFormat;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;
public class StubMapper extends Mapper<LongWritable, Text, Text, MinMaxCountTuple> {
private Text outUserId = new Text();
private MinMaxCountTuple outTuple = new MinMaxCountTuple();
private final static SimpleDateFormat frmt =
new SimpleDateFormat("yyyy-MM--dd'T'HH:mm:ss.SSS");
// public static HashMap<String, String> getMapFromCSV(String filePath) throws IOException
// {
//
// HashMap<String, String> words = new HashMap<String, String>();
//
// /*BufferedReader in = new BufferedReader(new FileReader(filePath));
//
// String line;
// //= in.readLine())
// while ((line = in.readLine()) != null) {
// String columns[] = line.split(",");
// if (!words.containsKey(columns[1])) {
// words.put(columns[1], columns[6]);
// }
//
// }
//
// return words;
//
// */
//
//
//
// String line=filePath;
//
// while(line!=null){
//
// String columns[] = line.split(",");
// if (columns.length>6){
// if (!words.containsKey(columns[1])) {
// words.put(columns[1], columns[6]);
// }
// }
//
// }
// return words;
// }
@Override
public void map(LongWritable key, Text value, Context context)
throws IOException, InterruptedException {
// HashMap<String, String> parsed = getMapFromCSV(value.toString());
//String columns[] = value.toString().split("\t");
// String strDate = parsed.get("CheckoutDateTime");
//String userId = columns[1];
//String strDate = columns[6];
if(value.toString().startsWith("BibNumber"))
{
return;
}
// String userId = parsed.get("BibNumber");
String data[] = value.toString().split(",",-1);
String userId = data[0];
String DateTime = data[5];
Date creationDate = frmt.parse(DateTime);
outTuple.setMin(creationDate);
outTuple.setMax(creationDate);
outTuple.setCount(1);
outUserId.set(userId);
context.write(outUserId, outTuple);
// TODO Auto-generated catch block
e.printStackTrace();
}
}
}
import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException;
import java.text.SimpleDateFormat;
import java.util.Date;
import org.apache.hadoop.io.Writable;
public class MinMaxCountTuple implements Writable{
private Date min = new Date();
private Date max = new Date();
private long count = 0;
private final static SimpleDateFormat frmt = new SimpleDateFormat("yyyy-MM-dd'T'HH:mm:ss.SSS");
public Date getMin()
{
return min;
}
public void setMin(Date min)
{
this.min = min;
}
public Date getMax()
{
return max;
}
public void setMax(Date max)
{
this.max = max;
}
public long getCount()
{
return count;
}
public void setCount(long count)
{
this.count = count;
}
@Override
public void write(DataOutput out) throws IOException {
// TODO Auto-generated method stub
out.writeLong(min.getTime());
out.writeLong(max.getTime());
out.writeLong(count);
}
public String toString()
{
return frmt.format(min) + "\t" + frmt.format(max) + "\t" + count;
}
@Override
public void readFields(DataInput in) throws IOException {
// TODO Auto-generated method stub
min = new Date(in.readLong());
max = new Date(in.readLong());
count = in.readLong();
}
}
这两个代码是mapper类和minmax类,它找到checkoutdate时间的最大值。基本上,我想要做的是获得一些日期将主要用于书籍的日期。所以,我只是在csv文件中使用key和value作为userId和checkoutdatetime。代码运行良好,但问题是映射器输入显示数据的大小,但是,mapper输出只有0大小的文件,这意味着它没有从输入获得一些输出。我不知道哪个部分是错的。我张贴了我的csv文件的屏幕截图。请赐教,真的很感激。谢谢。如果您需要有关我的代码的更多信息,请告诉我,我会提供更多信息。
18/03/30 01:38:41 INFO mapred.JobClient: Map input records=3794727
18/03/30 01:38:41 INFO mapred.JobClient: Map output records=0
18/03/30 01:38:41 INFO mapred.JobClient: Map output bytes=0
18/03/30 01:38:41 INFO mapred.JobClient: Input split bytes=416
18/03/30 01:38:41 INFO mapred.JobClient: Combine input records=0
18/03/30 01:38:41 INFO mapred.JobClient: Combine output records=0
18/03/30 01:38:41 INFO mapred.JobClient: Reduce input groups=0
18/03/30 01:38:41 INFO mapred.JobClient: Reduce shuffle bytes=24
18/03/30 01:38:41 INFO mapred.JobClient: Reduce input records=0
18/03/30 01:38:41 INFO mapred.JobClient: Reduce output records=0
答案 0 :(得分:1)
Mapper代码看起来很好。您是否在驱动程序中明确添加了输出键和输出值。
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(MinMaxCountTuple.class);
如果驱动程序中未提及,则可以尝试。